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Reasons for incredible Python growth

Doesn’t matter whether you are an IT developer or want to improve the quality of business with IT innovations, you will ask the same question – which programming language to choose. During different periods there were diverse opinions on that point, Java, C++, Ruby were on the high level. And today we follow the rapid development of the Python, in this article, we will review the reasons why this language is so popular.

What is Python?

The language was created in the 1980s, but due to a lack of marketing, didn’t reach its level of popularity until the 21st century. Then, some major problems of the language were solved, and Python became a powerful coding platform. The popularity of this programming language is so high due to the fact that developers can build a top-notch software with increased productivity.

Why is Python so popular?

Creation of Python was inspired by C++ and Java, which means those languages have similar features. This programming language which ought to increase the productivity of IT engineers. It can be used for web development, games, mobile development, automatization scripts, complex accounting systems, and many others. So, several benefits are obvious: the coding process is simple due to its universality, Python is easy for understanding and learning, as an outcome the cost of production is decreased and quality is increased.

Python is famous for its efficiency, speed, reliability, and quality, which are on the same level of skill. An application can be created under any circumstances and end up with an amazing performance. It has the potential to develop a corporate standard for high-security applications using 128-bit encryption technology. In addition, multi-channel security measures will be implemented to the application.

Differences Between Ruby and Python

Rewind a bit further, before Big Data was a real “thing”, and you would have seen a heated battle between Ruby and Python to become “the language of the web”. Both proved well suited for developing web applications.

Python was already reasonably well entrenched in academia and a handful of disparate industries. The closest Python equivalent to Rails was Django. Despite being released slightly ahead of Rails, it seemed to lag in popularity by a wide margin.

Python has quietly become an incredibly compelling language on which to build numerical computing libraries given that C extensions can share and manipulate data with very little overhead;

Python and Ruby fight it out on the web, where most assume the “language war” would be won;

as magnetic storage device prices plummet, it becomes feasible to store enormous amounts of data for later analysis (even if it’s not clear what that analysis might entail, better to just save the data since it has become cheap enough to do so);

the need for a new breed of programmer emerges: one with a background in statistics and/or applied math and little prior programming experience;

Data Scientists, looking for a language that is both expressive and fast (with good numerical computing library support to boot) all settle on Python.

Many felt that the languages were similar enough in expressiveness and approachability that one would ultimately “win” the web. But there was a fundamental difference in the implications of such an idea: while Ruby’s popularity was closely intertwined with that of Rails, Django represented a comparatively small percentage of an already vibrant Python ecosystem. Ruby, it seemed, needed Rails to “beat” Python to guarantee its continued popularity, and in many ways it did.

Python in Action

It just turned out to be the case that the “web wars” mattered far less than anyone anticipated. A lot of powerful and popular platforms have been created with the Python:

Google

Dropbox

Mozilla

Facebook

Yandex

Dropbox Dropbox Client

Reddit

Instagram

Quora

Spotify

Python continues to be a leading tool in a number of niches:

development of web applications (here we have an unconditional leader in the form of Django);

data analysis and machine learning;

rapid prototyping of ideas in business due to the abundance of ready-made libraries, low entry threshold in the language and high productivity of software written in Python;

writing scripts to automate tasks.

What does it tell us about? About many things, and the most important is that large corporations are not afraid to build their business around the Python. They are confident that the technology will live and keep on developing. Moreover, the variety of applications is also encouraging, which indicates a wide range of tasks that Python solves masterfully.

Summing up

Taking into account the features described above, we can conclude that Python is powerful for both, learning and software development. This platform includes efficiency, reliability, security, and simplicity. So, asking yourself a question – which language to choose for your future project, or from what to start learning to programme, the answer is obvious – Python.